Yaoqi Zhou
Orcid: 0000-0002-9958-5699
According to our database1,
Yaoqi Zhou
authored at least 69 papers
between 2005 and 2024.
Collaborative distances:
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Bibliography
2024
MARS and RNAcmap3: The Master Database of All Possible RNA Sequences Integrated with RNAcmap for RNA Homology Search.
Genom. Proteom. Bioinform., 2024
2023
SPIN-CGNN: Improved fixed backbone protein design with contact map-based graph construction and contact graph neural network.
PLoS Comput. Biol., December, 2023
CAID prediction portal: a comprehensive service for predicting intrinsic disorder and binding regions in proteins.
Nucleic Acids Res., July, 2023
Fast and accurate protein intrinsic disorder prediction by using a pretrained language model.
Briefings Bioinform., July, 2023
EVlncRNA-Dpred: improved prediction of experimentally validated lncRNAs by deep learning.
Briefings Bioinform., January, 2023
2022
Predicting RNA distance-based contact maps by integrated deep learning on physics-inferred secondary structure and evolutionary-derived mutational coupling.
Bioinform., 2022
SPOT-Contact-LM: improving single-sequence-based prediction of protein contact map using a transformer language model.
Bioinform., 2022
Probing RNA structures and functions by solvent accessibility: an overview from experimental and computational perspectives.
Briefings Bioinform., 2022
2021
EVLncRNAs 2.0: an updated database of manually curated functional long non-coding RNAs validated by low-throughput experiments.
Nucleic Acids Res., 2021
DescribePROT: database of amino acid-level protein structure and function predictions.
Nucleic Acids Res., 2021
RNA Backbone Torsion and Pseudotorsion Angle Prediction Using Dilated Convolutional Neural Networks.
J. Chem. Inf. Model., 2021
RNAcmap: a fully automatic pipeline for predicting contact maps of RNAs by evolutionary coupling analysis.
Bioinform., 2021
Structure-aware protein-protein interaction site prediction using deep graph convolutional network.
Bioinform., 2021
Improved RNA secondary structure and tertiary base-pairing prediction using evolutionary profile, mutational coupling and two-dimensional transfer learning.
Bioinform., 2021
SPOT-1D-Single: improving the single-sequence-based prediction of protein secondary structure, backbone angles, solvent accessibility and half-sphere exposures using a large training set and ensembled deep learning.
Bioinform., 2021
De novo protein design by an energy function based on series expansion in distance and orientation dependence.
Bioinform., 2021
Single-sequence and profile-based prediction of RNA solvent accessibility using dilated convolutional neural network.
Bioinform., 2021
SPOT-1D2: Improving Protein Secondary Structure Prediction using High Sequence Identity Training Set and an Ensemble of Recurrent and Residual-convolutional Neural Networks.
Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2021
DeepANIS: Predicting antibody paratope from concatenated CDR sequences by integrating bidirectional long-short-term memory and transformer neural networks.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
2020
SPOT-Fold: Fragment-Free Protein Structure Prediction Guided by Predicted Backbone Structure and Contact Map.
J. Comput. Chem., 2020
All-Atom Knowledge-Based Potential for RNA Structure Discrimination Based on the Distance-Scaled Finite Ideal-Gas Reference State.
J. Comput. Biol., 2020
Getting to Know Your Neighbor: Protein Structure Prediction Comes of Age with Contextual Machine Learning.
J. Comput. Biol., 2020
Bioinform., 2020
Identifying molecular recognition features in intrinsically disordered regions of proteins by transfer learning.
Bioinform., 2020
Erratum to: Large expert-curated database for benchmarking document similarity detection in biomedical literature search.
Database J. Biol. Databases Curation, 2020
2019
Improved fragment sampling for ab initio protein structure prediction using deep neural networks.
Nat. Mach. Intell., 2019
SPOT-Peptide: Template-Based Prediction of Peptide-Binding Proteins and Peptide-Binding Sites.
J. Chem. Inf. Model., 2019
DLIGAND2: an improved knowledge-based energy function for protein-ligand interactions using the distance-scaled, finite, ideal-gas reference state.
J. Cheminformatics, 2019
SPOT-Disorder2: Improved Protein Intrinsic Disorder Prediction by Ensembled Deep Learning.
Genom. Proteom. Bioinform., 2019
SPRINT-Gly: predicting N- and O-linked glycosylation sites of human and mouse proteins by using sequence and predicted structural properties.
Bioinform., 2019
Improving prediction of protein secondary structure, backbone angles, solvent accessibility and contact numbers by using predicted contact maps and an ensemble of recurrent and residual convolutional neural networks.
Bioinform., 2019
Large expert-curated database for benchmarking document similarity detection in biomedical literature search.
Database J. Biol. Databases Curation, 2019
2018
EVLncRNAs: a manually curated database for long non-coding RNAs validated by low-throughput experiments.
Nucleic Acids Res., 2018
Detecting Proline and Non-Proline Cis Isomers in Protein Structures from Sequences Using Deep Residual Ensemble Learning.
J. Chem. Inf. Model., 2018
Accurate Single-Sequence Prediction of Protein Intrinsic Disorder by an Ensemble of Deep Recurrent and Convolutional Architectures.
J. Chem. Inf. Model., 2018
Predicting lysine-malonylation sites of proteins using sequence and predicted structural features.
J. Comput. Chem., 2018
Single-sequence-based prediction of protein secondary structures and solvent accessibility by deep whole-sequence learning.
J. Comput. Chem., 2018
<i>B</i>-factor profile prediction for RNA flexibility using support vector machines.
J. Comput. Chem., 2018
Grid-based prediction of torsion angle probabilities of protein backbone and its application to discrimination of protein intrinsic disorder regions and selection of model structures.
BMC Bioinform., 2018
Bioinform., 2018
Accurate prediction of protein contact maps by coupling residual two-dimensional bidirectional long short-term memory with convolutional neural networks.
Bioinform., 2018
Sixty-five years of the long march in protein secondary structure prediction: the final stretch?
Briefings Bioinform., 2018
2017
J. Comb. Optim., 2017
DisBind: A database of classified functional binding sites in disordered and structured regions of intrinsically disordered proteins.
BMC Bioinform., 2017
LRFragLib: an effective algorithm to identify fragments for de novo protein structure prediction.
Bioinform., 2017
SPOT-ligand 2: improving structure-based virtual screening by binding-homology search on an expanded structural template library.
Bioinform., 2017
Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility.
Bioinform., 2017
Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks.
Bioinform., 2017
2016
Sequence-Based Prediction of Protein-Carbohydrate Binding Sites Using Support Vector Machines.
J. Chem. Inf. Model., 2016
SPOT-Ligand: Fast and effective structure-based virtual screening by binding homology search according to ligand and receptor similarity.
J. Comput. Chem., 2016
J. Comput. Chem., 2016
Sequence-based prediction of protein-peptide binding sites using support vector machine.
J. Comput. Chem., 2016
sDFIRE: Sequence-specific statistical energy function for protein structure prediction by decoy selections.
J. Comput. Chem., 2016
Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins.
Bioinform., 2016
Predicting the errors of predicted local backbone angles and non-local solvent- accessibilities of proteins by deep neural networks.
Bioinform., 2016
Fast and accurate non-sequential protein structure alignment using a new asymmetric linear sum assignment heuristic.
Bioinform., 2016
2015
DDIG-in: detecting disease-causing genetic variations due to frameshifting indels and nonsense mutations employing sequence and structural properties at nucleotide and protein levels.
Bioinform., 2015
2014
Carbohydrate-binding protein identification by coupling structural similarity searching with binding affinity prediction.
J. Comput. Chem., 2014
Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network.
J. Comput. Chem., 2014
LEAP: Highly accurate prediction of protein loop conformations by integrating coarse-grained sampling and optimized energy scores with all-atom refinement of backbone and side chains.
J. Comput. Chem., 2014
2012
SPINE X: Improving protein secondary structure prediction by multistep learning coupled with prediction of solvent accessible surface area and backbone torsion angles.
J. Comput. Chem., 2012
2011
Protein side chain modeling with orientation-dependent atomic force fields derived by series expansions.
J. Comput. Chem., 2011
BMC Bioinform., 2011
Improving protein fold recognition and template-based modeling by employing probabilistic-based matching between predicted one-dimensional structural properties of query and corresponding native properties of templates.
Bioinform., 2011
2010
Structure-based prediction of DNA-binding proteins by structural alignment and a volume-fraction corrected DFIRE-based energy function.
Bioinform., 2010
2005
Web-based toolkits for topology prediction of transmembrane helical proteins, fold recognition, structure and binding scoring, folding-kinetics analysis and comparative analysis of domain combinations.
Nucleic Acids Res., 2005
SCUD: Fast structure clustering of decoys using reference state to remove overall rotation.
J. Comput. Chem., 2005
Fold Helical Proteins by Energy Minimization in Dihedral Space and a Dfire-based Statistical Energy Function.
J. Bioinform. Comput. Biol., 2005
SPEM: improving multiple sequence alignment with sequence profiles and predicted secondary structures.
Bioinform., 2005